Sodium in School Lunches Before and After Implementation of the Healthy, Hunger Free Kids Act of 2010

Thesis (Master's)--University of Washington, 2016-08

Giving the benefit of the doubt: the role of vulnerability in the perception of Dark Triad behaviours.

The 'Dark Triad' of socially aversive personality traits (Machiavellianism, Narcissism, and Psychopathy) is typically associated with grandiosity, callousness, and exploitation. Despite this, people with such traits can be very successful in life, especially in the occupational context. This study investigated the characteristics of individuals who enable and abet people high on Dark Triad traits (e.g. through tolerating unpleasant behaviours, not challenging unethical conduct, etc.). High Dark Triad individuals may be able to identify individuals who are susceptible to social manipulation and who are therefore less likely to challenge their behaviours. This study used a 20-item Vulnerability Scale to capture the characteristics of individuals who fall victim to people high on the Dark Triad traits. Cronbach's alpha for the Vulnerability Scale was .80. Pearson's correlation between total vulnerability scores and each of the Big Five personality traits revealed that predictors of vulnerability to social manipulation include low extraversion, low conscientiousness, high neuroticism, and high agreeableness. The vignette method was used to elicit perceptions of Dark Triad behaviours from those who are found to demonstrate signs of social vulnerability. Differences in response styles on Likert-type statements and open-ended questions were found between the high and low vulnerability groups.

Urban Retrofit and Resilience: The challenge of Energy Efficiency and Vulnerability

Urban retrofit is becoming increasingly established as one of the most effective solutions to contain the energy consumption of the existing building stock, to reduce vulnerability to natural and man-made risk and generally improve the quality of built space. However, the planning of retrofit interventions at urban scale should take account of the actual feasibility of measures lest they remain only on paper. This contribution supplies an overview of the many issues related to the subject of urban regeneration, proposing a procedure to identify practical interventions to minimize costs and maximize benefits, in terms of energy efficiency, an increase in resilience and improvement in the quality of the building stock. This procedure was applied to a case study of a neighborhood in the city of Naples, a high-density urban area which is particularly vulnerable to volcanic and seismic risk, and to risks due to climate change.

Assessing and reducing vulnerability to climate change: Moving from theory to practical decision-support

As climate change continues to impact socio-ecological systems, tools that assist conservation managers to understand vulnerability and target adaptations are essential. Quantitative assessments of vulnerability are rare because available frameworks are complex and lack guidance for dealing with data limitations and integrating across scales and disciplines. This paper describes a semi-quantitative method for assessing vulnerability to climate change that integrates socio-ecological factors to address management objectives and support decision-making. The method applies a framework first adopted by the Intergovernmental Panel on Climate Change and uses a structured 10-step process. The scores for each framework element are normalized and multiplied to produce a vulnerability score and then the assessed components are ranked from high to low vulnerability. Sensitivity analyses determine which indicators most influence the analysis and the resultant decision-making process so data quality for these indicators can be reviewed to increase robustness. Prioritisation of components for conservation considers other economic, social and cultural values with vulnerability rankings to target actions that reduce vulnerability to climate change by decreasing exposure or sensitivity and/or increasing adaptive capacity. This framework provides practical decision-support and has been applied to marine ecosystems and fisheries, with two case applications provided as examples: (1) food security in Pacific Island nations under climate-driven fish declines, and (2) fisheries in the Gulf of Carpentaria, northern Australia. The step-wise process outlined here is broadly applicable and can be undertaken with minimal resources using existing data, thereby having great potential to inform adaptive natural resource management in diverse locations.

A CSR communication strategy for Ibersol: fighting hunger in Portugal

Field lab in marketing

Does social vulnerability for caries predict caries status of children in sub-urban Nigeria?

It is important to identify groups of people vulnerable to a disease condition. Aim: To determine the association between social vulnerability to caries and caries status of children in Ile-Ife, Nigeria. Methods: A composite vulnerability index for caries was developed using data generated for 992 children. Wilks’ Lambda test to verify relationship between vulnerability and its variables. Logistic regression analysis was conducted to determine if the social vulnerability for caries index was a good predictor for caries status. Results: The social vulnerability to caries index could not predict caries status. The study found that sex, age and number of siblings were the significant predictors of caries status in the study population. Females (AOR: 1.63; 95%CI: 1.08 – 2.46; p=0.02) and children with more than two siblings had higher odds of having caries (AOR: 2.61; 95%CI: 1.61 – 4.24; p<0.001) while children below 5 years had lower odds of having caries (AOR: 0.62; 95%CI: 0.39 – 1.00; p=0.05) Conclusions: The social vulnerability index for caries could not predict the caries status of children in the study population. Sensitive tools to identify children with caries in the study population should be developed.

The vulnerability of aquatic systems of the Upper Napo River Basin (Ecuadorian Amazon) to human activities

Aquatic ecosystems exhibit different vulnerabilities to anthropogenic disturbances. I examined this problem in the Upper Napo River Basin (UNRB), Ecuador. I ranked from 1 to 5 aquatic ecosystem uniqueness, health and threats. I stratified the basin into five Ecological Drainage Units (EDU), 48 Aquatic Ecological Systems (AES), and 203 macrohabitats. I found main threats (habitat conversion/degradation, land development, mining, oil industries, and water diversion) cover 54% of the UNRB, but have different scores and extents in each EDU. I assessed the health of 111 AESs, under three land use treatments, by analyzing the streamside zone, physical forms, water quality, aquatic life, and hydrology. Overall, health of AESs varied from 5 to 2.58, with 5 being the highest level of health. Threats and health of AESs were inversely related (F=34.119, P

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder

Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.

2013 survey of Iowa groundwater and evaluation of public well vulnerability classifications for contaminants of emerging concern (2015)

Studies in Iowa have long documented the vulnerability of wells with less than 50 feet (15 meters) of confining materials above the source aquifer to contamination from nitrate and various pesticides. Recent studies in Wisconsin have documented the occurrence of viruses in untreated groundwater, even in wells considered to have little vulnerability to contamination from near-surface activities. In addition, sensitive methods have become available for analyses of pharmaceuticals and pesticides. This study represents the first comprehensive examination of contaminants of emerging concern in Iowa’s groundwater conducted to date, and one of the first conducted in the United States. Raw groundwater samples were collected from 66 public supply wells during the spring of 2013, when the state was recovering from drought conditions. Samples were analyzed for 206 chemical and biological parameters; including 20 general water-quality parameters and major ions, 19 metals, 5 nutrients, 10 virus groups, 3 species of pathogenic bacteria, 5 microbial indicators, 108 pharmaceuticals, 35 pesticides and pesticide degradates, and tritium. The wells chosen for this study represent a diverse range of ages, depths, confining material thicknesses, pumping rates, and land use settings. The most commonly detected contaminant group was pesticide compounds, which were present in 41% of the samples. As many as 6 pesticide compounds were found together in a sample, most of which were chloroacetanilide degradates. While none of the measured concentrations of pesticide compounds exceeded current benchmark levels, several of these compounds are listed on the U.S. Environmental Protection Agency’s Contaminant Candidate List and could be subject to drinking water standards in the future. Despite heavy use in the past decade, glyphosate was not detected, and its metabolite, aminomethylphosphonic acid, was only detected in two of 60 wells tested (3%) at the detection limit of 0.02 μg/L. Pharmaceutical compounds were detected in 35% of 63 samples. Of the 14 pharmaceuticals detected, six had reported concentrations above the method reporting limit, with the maximum reported concentration of 826 ng/L for acetaminophen. Diphenhydramine was the only pharmaceutical to have two detections above the reporting limit, at 24.5 and 145 ng/L. Eight pharmaceuticals had confirmed detections at concentrations below the method reporting limit. Caffeine was the most frequently detected pharmaceutical compound (25%), followed by the caffeine metabolite, 1,7-dimethylxanthine (16%). Microorganisms were detected in 21% of the wells using quantitative polymerase chain reaction methodologies. The most frequently detected microorganism was the pepper mild mottle virus (PMMV), a plant pathogen found in human waste. PMMV was detected in 17% of samples at concentrations ranging from 0.4 to 6.38 gene copies per liter. GII norovirus, human polyomavirus, bovine polyomavirus, and Campylobacter were also detected, while adenovirus, enterovirus, GI norovirus, swine hepatitis E, Salmonella, and enterohemmorhagic E. coli were not detected. No correlations were found between viruses or pathogenic bacteria and microbial indicators. Wells with less than 50 feet (15 meters) of confining material were shown to have greater incidence of surface-related contaminants; however, significant relationships (p<0.05) between confining layer thickness and contaminants were only found for nitrate and herbicides.

A new approach for computing a flood vulnerability index using cluster analysis

A Flood Vulnerability Index (FloodVI) was developed using Principal Component Analysis (PCA) and a new aggregation method based on Cluster Analysis (CA). PCA simplifies a large number of variables into a few uncorrelated factors representing the social, economic, physical and environmental dimensions of vulnerability. CA groups areas that have the same characteristics in terms of vulnerability into vulnerability classes. The grouping of the areas determines their classification contrary to other aggregation methods in which the areas' classification determines their grouping. While other aggregation methods distribute the areas into classes, in an artificial manner, by imposing a certain probability for an area to belong to a certain class, as determined by the assumption that the aggregation measure used is normally distributed, CA does not constrain the distribution of the areas by the classes. FloodVI was designed at the neighbourhood level and was applied to the Portuguese municipality of Vila Nova de Gaia where several flood events have taken place in the recent past. The FloodVI sensitivity was assessed using three different aggregation methods: the sum of component scores, the first component score and the weighted sum of component scores. The results highlight the sensitivity of the FloodVI to different aggregation methods. Both sum of component scores and weighted sum of component scores have shown similar results. The first component score aggregation method classifies almost all areas as having medium vulnerability and finally the results obtained using the CA show a distinct differentiation of the vulnerability where hot spots can be clearly identified. The information provided by records of previous flood events corroborate the results obtained with CA, because the inundated areas with greater damages are those that are identified as high and very high vulnerability areas by CA. This supports the fact that CA provides a reliable FloodVI.

Avian trait-mediated vulnerability to road traffic collisions

Collision with vehicles is an important source of bird mortality, but it is uncertain why some species are killed more often than others. Focusing on passerines,we testedwhether mortality is associated with bird abundances, and with traits reflecting flight manoeuvrability, habitat, diet, and foraging and social behaviours. We also tested whether the species most vulnerable to road-killing were scarcer near (b500 m) or far (N500–5000 m) from roads. During the breeding seasons of 2009–2011,we surveyed roadkills daily along 50 km of roads, and estimated bird abundances from 74 point counts. After correcting for phylogenetic relatedness, there was strong correlation between roadkill numbers and the abundances of 28 species counted near roads. However, selectivity indices indicated that Blue tit (Parus caeruleus), Blackcap (Sylvia atricapilla) and European goldfinch (Carduelis carduelis) were significantly more road-killed than expected from their abundances, while the inverse was found for seven species. Using phylogenetic generalised estimating equations, we found that selectivity indexes were strongly related to foraging behaviour and habitat type, and weakly so to body size, wing load, diet and social behaviour. The most vulnerable passerines were foliage/bark and swoop foragers, inhabiting woodlands, with small body size and low wing load. The species most vulnerable to road collisions were not scarcer close to roads. Overall, our study suggests that traits provide a basis to identify the passerine species most vulnerable to road collisions, which may be priority targets for future research on the population-level effects of roadkills.

Proposal for Labor Market Integration of Teachers in Contexts of High Social Vulnerability

The purpose of this paper is to share a proposal for teacher’s labor market integration in contexts of high social5 vulnerability. This paper is the result of a research conducted in a priority attention primary school6 of the central canton of Heredia7. It explored the labor market integration process of teachers, considering the community, family and student reality of a population social risk. The research that supports this proposal is based on a qualitative approach, since the diagnosis process is not intended to provide answers that could be commonly applied to other education centers in similar contexts, but to make an exploratory approach of teachers’ reality and their integration process into education institutions of high social vulnerability. Therefore, although this paper intends to share this experience, it does not aim to unify integration practices, but to be an input in carrying out similar processes.  (5) The concept of high social vulnerability is understood based on Sojo’s approach (2003), which defines it as marginal urban communities in areas considered by the Costa Rican government as priority areas with the greatest social, economic backwardness in the country, and high rates of violence, leisure, unemployment and drug addiction. (6) Translator’s note: The Costa Rican education system is composed of primary education (1st-6th grade) and secondary education (7th-11th grade). (7)A public primary school in the circuit 02 of the Province of Heredia.